removed pics

Reviewed-on: #1

src/camera.py

@@ -1,22 +1,183 @@
 import cv2
+import subprocess
+import re
+
+
+def detect_camera_modes(device_id=0):
+    """
+    Detect available camera resolutions using v4l2-ctl.
+    Returns dict of modes sorted by resolution (smallest to largest).
+    """
+    modes = {}
+    
+    try:
+        # Run v4l2-ctl to get supported formats
+        device = f"/dev/video{device_id}"
+        result = subprocess.run(
+            ['v4l2-ctl', '--device', device, '--list-formats-ext'],
+            capture_output=True,
+            text=True,
+            timeout=5
+        )
+        
+        if result.returncode != 0:
+            print(f"v4l2-ctl failed: {result.stderr}")
+            return _get_fallback_modes()
+        
+        # Parse output for "Size: Discrete WxH" lines
+        # Example: "Size: Discrete 2592x1944"
+        size_pattern = re.compile(r'Size:\s+Discrete\s+(\d+)x(\d+)')
+        
+        resolutions = set()  # Use set to avoid duplicates
+        for line in result.stdout.split('\n'):
+            match = size_pattern.search(line)
+            if match:
+                width = int(match.group(1))
+                height = int(match.group(2))
+                resolutions.add((width, height))
+        
+        if not resolutions:
+            print("No resolutions found in v4l2-ctl output")
+            return _get_fallback_modes()
+        
+        # Sort by total pixels (width * height)
+        sorted_res = sorted(resolutions, key=lambda r: r[0] * r[1])
+        
+        # Build modes dict with descriptive names
+        for i, (width, height) in enumerate(sorted_res):
+            pixels = width * height
+            
+            # Generate a name based on position/size
+            if i == 0:
+                name = 'low'
+                desc = 'Low'
+            elif i == len(sorted_res) - 1:
+                name = 'high'
+                desc = 'High'
+            elif len(sorted_res) == 3 and i == 1:
+                name = 'medium'
+                desc = 'Medium'
+            else:
+                name = f'res_{width}x{height}'
+                desc = f'{width}x{height}'
+            
+            modes[name] = {
+                'width': width,
+                'height': height,
+                'label': f'{width}x{height} ({desc})'
+            }
+        
+        print(f"Detected {len(modes)} camera modes: {list(modes.keys())}")
+        return modes
+        
+    except FileNotFoundError:
+        print("v4l2-ctl not found, using fallback modes")
+        return _get_fallback_modes()
+    except subprocess.TimeoutExpired:
+        print("v4l2-ctl timed out, using fallback modes")
+        return _get_fallback_modes()
+    except Exception as e:
+        print(f"Error detecting camera modes: {e}")
+        return _get_fallback_modes()
+
+
+def _get_fallback_modes():
+    """Fallback modes if v4l2-ctl detection fails"""
+    return {
+        'low': {'width': 640, 'height': 480, 'label': '640x480 (Low)'},
+        'medium': {'width': 1280, 'height': 960, 'label': '1280x960 (Medium)'},
+        'high': {'width': 1920, 'height': 1080, 'label': '1920x1080 (High)'},
+    }
+
 
 class Camera:
-    def __init__(self, device_id=0):
+    prevFrame = {}
+    def __init__(self, device_id=0, mode=None):
+        self.device_id = device_id
+        
+        # Detect available modes before opening camera
+        self.MODES = detect_camera_modes(device_id)
+        
+        # Open camera
         self.cap = cv2.VideoCapture(device_id)
         
         if not self.cap.isOpened():
             raise RuntimeError("Could not open camera, stop program")
         
+        # Default to highest resolution if no mode specified
+        if mode is None:
+            mode = list(self.MODES.keys())[0]  # Last = highest res
+        
+        self.current_mode = mode
+        self._apply_mode(mode)
+        
         # set resolution
         # self.cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1920)
         # self.cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080)
-        
+        self.cap.set(cv2.CAP_PROP_AUTO_EXPOSURE, 0)  # Disable auto-exposure
+        self.cap.set(cv2.CAP_PROP_EXPOSURE, -6)       # Set fixed exposure
+        self.cap.set(cv2.CAP_PROP_AUTO_WB, 0)         # Disable auto white balance
         self.window_name = "AutoScope"
     
+    def _apply_mode(self, mode_name):
+        """Apply resolution settings"""
+        if mode_name not in self.MODES:
+            print(f"Unknown mode {mode_name}, using first available")
+            mode_name = list(self.MODES.keys())[0]
+        
+        mode = self.MODES[mode_name]
+        
+        # Set resolution
+        self.cap.set(cv2.CAP_PROP_FRAME_WIDTH, mode['width'])
+        self.cap.set(cv2.CAP_PROP_FRAME_HEIGHT, mode['height'])
+        
+        self.current_mode = mode_name
+        
+        # Verify settings took effect
+        actual_w = int(self.cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+        actual_h = int(self.cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+        actual_fps = self.cap.get(cv2.CAP_PROP_FPS)
+        
+        print(f"Camera mode: {mode['label']}")
+        print(f"  Actual: {actual_w}x{actual_h} @ {actual_fps:.1f}fps")
+        
+        return actual_w, actual_h, actual_fps
+    
+    def set_mode(self, mode_name):
+        """Change camera mode (resolution/framerate)"""
+        return self._apply_mode(mode_name)
+    
+    def get_mode(self):
+        """Get current mode name"""
+        return self.current_mode
+    
+    def get_mode_info(self):
+        """Get current mode details"""
+        return self.MODES.get(self.current_mode, list(self.MODES.values())[0])
+    
+    def get_resolution(self):
+        """Get current actual resolution"""
+        w = int(self.cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+        h = int(self.cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+        return w, h
+    
+    def get_fps(self):
+        """Get current actual FPS"""
+        return self.cap.get(cv2.CAP_PROP_FPS)
+    
+    def get_available_modes(self):
+        """Get list of available mode names"""
+        return list(self.MODES.keys())
+    
+    def get_mode_labels(self):
+        """Get mode labels for UI"""
+        return {k: v['label'] for k, v in self.MODES.items()}
+    
     def capture_frame(self):
         ret, frame = self.cap.read()
         if not ret:
-            raise RuntimeError("Failed to capture frame, stop program")
+            return prevframe
+        prevframe = frame
         return frame
     
     def show_frame(self, frame):
@@ -69,4 +230,3 @@ class Camera:
                 break
         
         self.close_window()
-    

src/stitching_scanner.py

@@ -0,0 +1,756 @@
+"""
+Stitching Scanner v2 - Simplified unified approach
+
+Same displacement-based stitching for both horizontal rows and vertical row transitions.
+No complex visual matching - just track displacement and append strips.
+"""
+
+import cv2
+import numpy as np
+import time
+import threading
+from dataclasses import dataclass
+from typing import Optional, Callable, Tuple
+from enum import Enum
+
+
+class ScanDirection(Enum):
+    RIGHT = 'right'
+    LEFT = 'left'
+    DOWN = 'down'
+    UP = 'up'
+
+
+@dataclass
+class StitchConfig:
+    displacement_threshold: float = 0.10  # 10% of frame triggers append
+    movement_interval: float = 0.001
+    frame_interval: float = 1.00
+    settle_time: float = 0.75
+    max_scan_time: float = 300.0
+    row_overlap: float = 0.15
+    max_mosaic_width: int = 15000
+    max_mosaic_height: int = 12000
+    scan_speed_index: int = 3
+    autofocus_every_row: bool = True
+
+
+@dataclass
+class StitchState:
+    is_scanning: bool = False
+    direction: str = ''
+    cumulative_x: float = 0.0
+    cumulative_y: float = 0.0
+    last_displacement: Tuple[float, float] = (0.0, 0.0)
+    current_row: int = 0
+    total_rows: int = 0
+    mosaic_width: int = 0
+    mosaic_height: int = 0
+    frame_count: int = 0
+    append_count: int = 0
+
+
+class StitchingScanner:
+    """
+    Slide scanner using continuous stitching.
+    Unified approach for horizontal and vertical movement.
+    """
+    
+    def __init__(self, camera, motion_controller, autofocus_controller=None,
+                 config: StitchConfig = None,
+                 on_log: Callable[[str], None] = None,
+                 on_progress: Callable[[int, int], None] = None,
+                 on_mosaic_updated: Callable[[], None] = None):
+        self.camera = camera
+        self.motion = motion_controller
+        self.autofocus = autofocus_controller
+        self.config = config or StitchConfig()
+        
+        self.on_log = on_log
+        self.on_progress = on_progress
+        self.on_mosaic_updated = on_mosaic_updated
+        
+        self.running = False
+        self.paused = False
+        self.state = StitchState()
+        self._state_lock = threading.Lock()
+        
+        self.mosaic: Optional[np.ndarray] = None
+        self._mosaic_lock = threading.Lock()
+        
+        self._prev_frame: Optional[np.ndarray] = None
+        self._displacement_since_append_x: float = 0.0
+        self._displacement_since_append_y: float = 0.0
+        
+        self._thread: Optional[threading.Thread] = None
+    
+    def log(self, message: str):
+        if self.on_log:
+            self.on_log(f"[Stitch] {message}")
+        print(f"[Stitch] {message}")
+    
+    # =========================================================================
+    # Displacement Detection
+    # =========================================================================
+    
+    def _to_grayscale(self, frame: np.ndarray) -> np.ndarray:
+        if len(frame.shape) == 3:
+            return cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+        return frame
+    
+    def _detect_displacement(self, prev_frame: np.ndarray, 
+                             curr_frame: np.ndarray) -> Tuple[float, float]:
+        prev_gray = self._to_grayscale(prev_frame)
+        curr_gray = self._to_grayscale(curr_frame)
+        
+        if prev_gray.shape != curr_gray.shape:
+            return (0.0, 0.0)
+        
+        prev_f = prev_gray.astype(np.float32)
+        curr_f = curr_gray.astype(np.float32)
+        
+        h, w = prev_gray.shape
+        window = cv2.createHanningWindow((w, h), cv2.CV_32F)
+        prev_f = prev_f * window
+        curr_f = curr_f * window
+        
+        shift, _ = cv2.phaseCorrelate(prev_f, curr_f)
+        return shift
+    
+    def _detect_displacement_robust(self, prev_frame: np.ndarray,
+                                   curr_frame: np.ndarray) -> Tuple[float, float]:
+        dx, dy = self._detect_displacement(prev_frame, curr_frame)
+        
+        h, w = prev_frame.shape[:2]
+        max_displacement = max(w, h) * 0.5
+        
+        if abs(dx) > max_displacement or abs(dy) > max_displacement:
+            self.log(f"Warning: Large displacement ({dx:.1f}, {dy:.1f}), ignoring")
+            return (0.0, 0.0)
+        
+        return (dx, dy)
+    
+    # =========================================================================
+    # Mosaic Building
+    # =========================================================================
+    
+    def _init_mosaic(self, frame: np.ndarray):
+        with self._mosaic_lock:
+            self.mosaic = frame.copy()
+        
+        self._prev_frame = frame.copy()
+        self._displacement_since_append_x = 0.0
+        self._displacement_since_append_y = 0.0
+        
+        with self._state_lock:
+            h, w = frame.shape[:2]
+            self.state.mosaic_width = w
+            self.state.mosaic_height = h
+            self.state.frame_count = 1
+            self.state.append_count = 0
+        
+        self.log(f"Initialized mosaic: {frame.shape[1]}x{frame.shape[0]}")
+    
+    def _blend_horizontal(self, base: np.ndarray, strip: np.ndarray, 
+                          blend_width: int, append_right: bool) -> np.ndarray:
+        if blend_width <= 0 or blend_width >= strip.shape[1]:
+            if append_right:
+                return np.hstack([base, strip])
+            return np.hstack([strip, base])
+        
+        h_base, w_base = base.shape[:2]
+        h_strip, w_strip = strip.shape[:2]
+        
+        if h_strip != h_base:
+            if append_right:
+                return np.hstack([base, strip])
+            return np.hstack([strip, base])
+        
+        blend_w = min(blend_width, w_strip, w_base)
+        
+        if append_right:
+            result_width = w_base + w_strip - blend_w
+            result = np.zeros((h_base, result_width, 3), dtype=np.uint8)
+            result[:, :w_base] = base
+            
+            alpha = np.linspace(1, 0, blend_w, dtype=np.float32)[np.newaxis, :, np.newaxis]
+            base_overlap = base[:, -blend_w:].astype(np.float32)
+            strip_overlap = strip[:, :blend_w].astype(np.float32)
+            blended = (base_overlap * alpha + strip_overlap * (1 - alpha)).astype(np.uint8)
+            
+            result[:, w_base - blend_w:w_base] = blended
+            result[:, w_base:] = strip[:, blend_w:]
+            return result
+        else:
+            result_width = w_base + w_strip - blend_w
+            result = np.zeros((h_base, result_width, 3), dtype=np.uint8)
+            result[:, :w_strip] = strip
+            
+            alpha = np.linspace(0, 1, blend_w, dtype=np.float32)[np.newaxis, :, np.newaxis]
+            strip_overlap = strip[:, -blend_w:].astype(np.float32)
+            base_overlap = base[:, :blend_w].astype(np.float32)
+            blended = (strip_overlap * (1 - alpha) + base_overlap * alpha).astype(np.uint8)
+            
+            result[:, w_strip - blend_w:w_strip] = blended
+            result[:, w_strip:] = base[:, blend_w:]
+            return result
+    
+    def _blend_vertical(self, base: np.ndarray, strip: np.ndarray,
+                        blend_height: int, append_below: bool) -> np.ndarray:
+        mh, mw = base.shape[:2]
+        sh, sw = strip.shape[:2]
+        
+        # Match widths
+        if sw > mw:
+            strip = strip[:, :mw]
+        elif sw < mw:
+            pad = np.zeros((sh, mw - sw, 3), dtype=np.uint8)
+            strip = np.hstack([strip, pad])
+        
+        blend_h = min(blend_height, sh, mh)
+        
+        if blend_h <= 0:
+            if append_below:
+                return np.vstack([base, strip])
+            return np.vstack([strip, base])
+        
+        if append_below:
+            alpha = np.linspace(1, 0, blend_h, dtype=np.float32)[:, np.newaxis, np.newaxis]
+            base_overlap = base[-blend_h:].astype(np.float32)
+            strip_overlap = strip[:blend_h].astype(np.float32)
+            blended = (base_overlap * alpha + strip_overlap * (1 - alpha)).astype(np.uint8)
+            
+            result_h = mh + sh - blend_h
+            result = np.zeros((result_h, mw, 3), dtype=np.uint8)
+            result[:mh - blend_h] = base[:-blend_h]
+            result[mh - blend_h:mh] = blended
+            result[mh:] = strip[blend_h:]
+            return result
+        else:
+            alpha = np.linspace(0, 1, blend_h, dtype=np.float32)[:, np.newaxis, np.newaxis]
+            strip_overlap = strip[-blend_h:].astype(np.float32)
+            base_overlap = base[:blend_h].astype(np.float32)
+            blended = (strip_overlap * (1 - alpha) + base_overlap * alpha).astype(np.uint8)
+            
+            result_h = mh + sh - blend_h
+            result = np.zeros((result_h, mw, 3), dtype=np.uint8)
+            result[:sh - blend_h] = strip[:-blend_h]
+            result[sh - blend_h:sh] = blended
+            result[sh:] = base[blend_h:]
+            return result
+    
+    def _append_strip(self, frame: np.ndarray, direction: ScanDirection):
+        """Append strip to mosaic based on accumulated displacement."""
+        BLEND_WIDTH = 10
+        SAFETY_MARGIN = 2
+        
+        with self._mosaic_lock:
+            if self.mosaic is None:
+                return
+            
+            h, w = frame.shape[:2]
+            mh, mw = self.mosaic.shape[:2]
+            
+            dx = abs(self._displacement_since_append_x)
+            dy = abs(self._displacement_since_append_y)
+            
+            if direction in [ScanDirection.RIGHT, ScanDirection.LEFT]:
+                append_width = round(dx) + SAFETY_MARGIN
+                append_width = min(append_width, w - BLEND_WIDTH - 5)
+                
+                if append_width < 1:
+                    return
+                
+                pixels_consumed = append_width - SAFETY_MARGIN
+                fractional_remainder = dx - pixels_consumed
+                
+                if direction == ScanDirection.RIGHT:
+                    strip_start = max(0, w - append_width - BLEND_WIDTH)
+                    new_strip = frame[:, strip_start:]
+                    self.mosaic = self._blend_horizontal(
+                        self.mosaic, new_strip, BLEND_WIDTH, append_right=True)
+                else:
+                    strip_end = min(w, append_width + BLEND_WIDTH)
+                    new_strip = frame[:, :strip_end]
+                    self.mosaic = self._blend_horizontal(
+                        self.mosaic, new_strip, BLEND_WIDTH, append_right=False)
+                
+                self._displacement_since_append_x = fractional_remainder
+                self._displacement_since_append_y = 0.0
+                    
+            elif direction in [ScanDirection.DOWN, ScanDirection.UP]:
+                append_height = round(dy) + SAFETY_MARGIN
+                append_height = min(append_height, h - BLEND_WIDTH - 5)
+                
+                if append_height < 1:
+                    return
+                
+                pixels_consumed = append_height - SAFETY_MARGIN
+                fractional_remainder = dy - pixels_consumed
+                
+                if direction == ScanDirection.DOWN:
+                    strip_end = min(h, append_height + BLEND_WIDTH)
+                    new_strip = frame[:strip_end:, :]
+                    self.mosaic = self._blend_vertical(
+                        self.mosaic, new_strip, BLEND_WIDTH, append_below=False)
+                else:
+                    strip_start = max(0, h - append_height - BLEND_WIDTH)
+                    new_strip = frame[:strip_start, :]
+                    self.mosaic = self._blend_vertical(
+                        self.mosaic, new_strip, BLEND_WIDTH, append_below=True)
+                
+                self._displacement_since_append_x = 0.0
+                self._displacement_since_append_y = fractional_remainder
+            
+            new_mh, new_mw = self.mosaic.shape[:2]
+        
+        with self._state_lock:
+            self.state.mosaic_width = new_mw
+            self.state.mosaic_height = new_mh
+            self.state.append_count += 1
+        
+        if self.on_mosaic_updated:
+            self.on_mosaic_updated()
+    
+    # =========================================================================
+    # Scan Control
+    # =========================================================================
+    
+    def start(self) -> bool:
+        if self.running:
+            self.log("Already running")
+            return False
+        
+        self.running = True
+        self.paused = False
+        
+        with self._state_lock:
+            self.state = StitchState()
+            self.state.is_scanning = True
+        
+        with self._mosaic_lock:
+            self.mosaic = None
+        
+        self._prev_frame = None
+        self._displacement_since_append_x = 0.0
+        self._displacement_since_append_y = 0.0
+        
+        self._thread = threading.Thread(target=self._scan_loop, daemon=True)
+        self._thread.start()
+        
+        self.log("Stitching scan started")
+        return True
+    
+    def stop(self):
+        self.running = False
+        self.paused = False
+        self.motion.stop_all()
+        
+        with self._state_lock:
+            self.state.is_scanning = False
+        
+        self.log("Scan stopped")
+    
+    def pause(self):
+        if self.running and not self.paused:
+            self.paused = True
+            self.motion.stop_all()
+            self.log("Scan paused")
+    
+    def resume(self):
+        if self.running and self.paused:
+            self.paused = False
+            self.log("Scan resumed")
+    
+    # =========================================================================
+    # Scanning Logic
+    # =========================================================================
+    
+    def _scan_loop(self):
+        try:
+            self.log("Starting scan loop")
+            self.log(f"Max dimensions: {self.config.max_mosaic_width}x{self.config.max_mosaic_height}")
+            
+            self.motion.set_speed(self.config.scan_speed_index)
+            time.sleep(0.1)
+            
+            frame = self._capture_frame()
+            self._init_mosaic(frame)
+            
+            row = 0
+            while self.running:
+                with self._state_lock:
+                    self.state.current_row = row
+                    self.state.total_rows = row + 1
+                
+                self.log(f"=== Row {row + 1} ===")
+                
+                # Serpentine: even rows right, odd rows left
+                h_direction = ScanDirection.RIGHT if row % 2 == 0 else ScanDirection.LEFT
+                
+                stop_reason = self._scan_direction(h_direction)
+                
+                if not self.running:
+                    break
+                
+                # Check max height
+                if self.state.mosaic_height >= self.config.max_mosaic_height:
+                    self.log(f"Max height reached ({self.state.mosaic_height}px)")
+                    break
+                
+                # Move to next row using same stitching approach
+                if not self._move_to_next_row():
+                    self.log("Failed to move to next row")
+                    break
+                
+                row += 1
+            
+            self.log(f"Scan complete! Final: {self.state.mosaic_width}x{self.state.mosaic_height}")
+            
+        except Exception as e:
+            self.log(f"Scan error: {e}")
+            import traceback
+            traceback.print_exc()
+        finally:
+            self.running = False
+            self.motion.stop_all()
+            with self._state_lock:
+                self.state.is_scanning = False
+    
+    def _scan_direction(self, direction: ScanDirection) -> str:
+        """Scan in a direction until edge or max dimension reached."""
+        self.log(f"Scanning {direction.value}...")
+        
+        with self._state_lock:
+            self.state.direction = direction.value
+        
+        frame = self._capture_frame()
+        h, w = frame.shape[:2]
+        
+        # Setup based on direction
+        if direction in [ScanDirection.RIGHT, ScanDirection.LEFT]:
+            threshold_pixels = w * self.config.displacement_threshold
+            max_dim = self.config.max_mosaic_width
+            current_dim = lambda: self.state.mosaic_width
+            start_cmd = 'E' if direction == ScanDirection.RIGHT else 'W'
+            stop_cmd = 'e' if direction == ScanDirection.RIGHT else 'w'
+        else:
+            threshold_pixels = h * self.config.displacement_threshold
+            max_dim = self.config.max_mosaic_height
+            current_dim = lambda: self.state.mosaic_height
+            start_cmd = 'S' if direction == ScanDirection.DOWN else 'N'
+            stop_cmd = 's' if direction == ScanDirection.DOWN else 'n'
+        
+        self._prev_frame = frame.copy()
+        self._displacement_since_append_x = 0.0
+        self._displacement_since_append_y = 0.0
+        
+        start_time = time.time()
+        no_movement_count = 0
+        max_no_movement = 50
+        stop_reason = 'stopped'
+        
+        while self.running and not self.paused:
+            if time.time() - start_time > self.config.max_scan_time:
+                self.log("Scan timeout")
+                stop_reason = 'timeout'
+                break
+            
+            if current_dim() >= max_dim:
+                self.log(f"Max dimension reached ({current_dim()}px)")
+                stop_reason = 'max_dim'
+                break
+            
+            # Pulse motor
+            self.motion.send_command(start_cmd)
+            time.sleep(self.config.movement_interval)
+            self.motion.send_command(stop_cmd)
+            
+            time.sleep(self.config.frame_interval)
+            
+            curr_frame = self._capture_frame()
+            dx, dy = self._detect_displacement_robust(self._prev_frame, curr_frame)
+            
+            self._displacement_since_append_x += dx
+            self._displacement_since_append_y += dy
+            
+            with self._state_lock:
+                self.state.cumulative_x = self._displacement_since_append_x
+                self.state.cumulative_y = self._displacement_since_append_y
+                self.state.last_displacement = (dx, dy)
+                self.state.frame_count += 1
+            
+            # Edge detection
+            movement = abs(dx) if direction in [ScanDirection.RIGHT, ScanDirection.LEFT] else abs(dy)
+            if movement < 1.0:
+                no_movement_count += 1
+                if no_movement_count >= max_no_movement:
+                    self.log(f"Edge detected (no movement)")
+                    stop_reason = 'edge'
+                    break
+            else:
+                no_movement_count = 0
+            
+            # Append when threshold reached
+            disp = abs(self._displacement_since_append_x) if direction in [ScanDirection.RIGHT, ScanDirection.LEFT] else abs(self._displacement_since_append_y)
+            if disp >= threshold_pixels:
+                self._append_strip(curr_frame, direction)
+                self.log(f"Appended {disp:.1f}px, mosaic: {self.state.mosaic_width}x{self.state.mosaic_height}")
+            
+            self._prev_frame = curr_frame.copy()
+            
+            if self.on_progress:
+                self.on_progress(self.state.append_count, 0)
+        
+        self.motion.send_command(stop_cmd)
+        time.sleep(self.config.settle_time)
+        self.log(f"Direction finished: {stop_reason}")
+        return stop_reason
+    
+    def _move_to_next_row(self) -> bool:
+        """
+        Move down to next row using displacement-based stitching.
+        Same approach as horizontal scanning.
+        """
+        self.log("Moving to next row...")
+        
+        frame = self._capture_frame()
+        h, w = frame.shape[:2]
+        
+        # Target: move (1 - overlap) * frame_height
+        target_displacement = h * (1 - self.config.row_overlap)
+        threshold_pixels = h * self.config.displacement_threshold
+        
+        self.log(f"Target Y: {target_displacement:.0f}px, threshold: {threshold_pixels:.0f}px")
+        
+        with self._state_lock:
+            self.state.direction = 'down'
+            self.state.cumulative_y = 0.0
+        
+        self._prev_frame = frame.copy()
+        self._displacement_since_append_x = 0.0
+        self._displacement_since_append_y = 0.0
+        
+        total_y = 0.0
+        no_movement_count = 0
+        max_no_movement = 30
+        
+        # Start moving South
+        self.motion.send_command('S')
+        
+        try:
+            while self.running:
+                time.sleep(self.config.frame_interval)
+                
+                curr_frame = self._capture_frame()
+                dx, dy = self._detect_displacement_robust(self._prev_frame, curr_frame)
+                
+                self._displacement_since_append_y += dy
+                total_y += dy
+                
+                with self._state_lock:
+                    self.state.cumulative_y = total_y
+                    self.state.last_displacement = (dx, dy)
+                
+                # Edge detection
+                if abs(dy) < 1.0:
+                    no_movement_count += 1
+                    if no_movement_count >= max_no_movement:
+                        self.log("Edge detected during row transition")
+                        self.motion.send_command('s')
+                        time.sleep(self.config.settle_time)
+                        return False
+                else:
+                    no_movement_count = 0
+                
+                # Append strip when threshold reached
+                if abs(self._displacement_since_append_y) >= threshold_pixels:
+                    self._append_strip(curr_frame, ScanDirection.DOWN)
+                    self.log(f"  Row transition: appended, total Y: {abs(total_y):.1f}px")
+                
+                # Done when we've moved enough
+                if abs(total_y) >= target_displacement:
+                    self.log(f"Row transition complete: {abs(total_y):.1f}px")
+                    self.motion.send_command('s')
+                    time.sleep(self.config.settle_time)
+                    
+                    # Reset for next horizontal row
+                    frame = self._capture_frame()
+                    self._prev_frame = frame.copy()
+                    self._displacement_since_append_x = 0.0
+                    self._displacement_since_append_y = 0.0
+                    return True
+                
+                self._prev_frame = curr_frame.copy()
+        
+        except Exception as e:
+            self.log(f"Row transition error: {e}")
+            self.motion.send_command('s')
+            return False
+        
+        self.motion.send_command('s')
+        time.sleep(self.config.settle_time)
+        return False
+    
+    def _capture_frame(self) -> np.ndarray:
+        frame = self.camera.capture_frame()
+        frame = cv2.rotate(frame, cv2.ROTATE_90_CLOCKWISE)
+        return frame
+    
+    # =========================================================================
+    # Getters
+    # =========================================================================
+    
+    def get_state(self) -> StitchState:
+        with self._state_lock:
+            return StitchState(
+                is_scanning=self.state.is_scanning,
+                direction=self.state.direction,
+                cumulative_x=self.state.cumulative_x,
+                cumulative_y=self.state.cumulative_y,
+                last_displacement=self.state.last_displacement,
+                current_row=self.state.current_row,
+                total_rows=self.state.total_rows,
+                mosaic_width=self.state.mosaic_width,
+                mosaic_height=self.state.mosaic_height,
+                frame_count=self.state.frame_count,
+                append_count=self.state.append_count
+            )
+    
+    def get_mosaic(self) -> Optional[np.ndarray]:
+        with self._mosaic_lock:
+            if self.mosaic is not None:
+                return self.mosaic.copy()
+            return None
+    
+    def get_mosaic_preview(self, max_size: int = 600) -> Optional[np.ndarray]:
+        with self._mosaic_lock:
+            if self.mosaic is None:
+                return None
+            
+            h, w = self.mosaic.shape[:2]
+            scale = min(max_size / w, max_size / h, 1.0)
+            
+            if scale < 1.0:
+                new_w = int(w * scale)
+                new_h = int(h * scale)
+                return cv2.resize(self.mosaic, (new_w, new_h))
+            
+            return self.mosaic.copy()
+    
+    def save_mosaic(self, filepath: str) -> bool:
+        with self._mosaic_lock:
+            if self.mosaic is None:
+                return False
+            cv2.imwrite(filepath, self.mosaic)
+            self.log(f"Saved mosaic to {filepath}")
+            return True
+    
+    # =========================================================================
+    # Testing
+    # =========================================================================
+    
+    def test_displacement(self, num_frames: int = 10) -> dict:
+        results = {'frames': [], 'total_dx': 0.0, 'total_dy': 0.0}
+        prev_frame = self._capture_frame()
+        
+        for i in range(num_frames):
+            time.sleep(0.1)
+            curr_frame = self._capture_frame()
+            dx, dy = self._detect_displacement(prev_frame, curr_frame)
+            results['frames'].append({'frame': i, 'dx': dx, 'dy': dy})
+            results['total_dx'] += dx
+            results['total_dy'] += dy
+            prev_frame = curr_frame
+        
+        return results
+    
+    def test_row_transition(self) -> dict:
+        """Test row transition using displacement stitching."""
+        results = {
+            'success': False,
+            'y_moved': 0.0,
+            'mosaic_before': (0, 0),
+            'mosaic_after': (0, 0),
+            'error': None
+        }
+        
+        try:
+            self.log("Testing row transition...")
+            
+            if self.mosaic is None:
+                frame = self._capture_frame()
+                self._init_mosaic(frame)
+            
+            results['mosaic_before'] = (self.state.mosaic_width, self.state.mosaic_height)
+            
+            with self._state_lock:
+                self.state.cumulative_y = 0.0
+            
+            self.running = True
+            success = self._move_to_next_row()
+            self.running = False
+            
+            results['success'] = success
+            results['y_moved'] = self.state.cumulative_y
+            results['mosaic_after'] = (self.state.mosaic_width, self.state.mosaic_height)
+            
+            self.log(f"Row transition: {'SUCCESS' if success else 'FAILED'}, Y: {results['y_moved']:.1f}px")
+            
+        except Exception as e:
+            results['error'] = str(e)
+            self.log(f"Test error: {e}")
+            self.running = False
+        
+        return results
+    
+    def test_single_row(self, direction: str = 'right') -> dict:
+        """Test scanning a single row."""
+        results = {
+            'success': False,
+            'stop_reason': None,
+            'appends': 0,
+            'mosaic_before': (0, 0),
+            'mosaic_after': (0, 0),
+            'error': None
+        }
+        
+        try:
+            self.log(f"Testing single row ({direction})...")
+            
+            if self.mosaic is None:
+                frame = self._capture_frame()
+                self._init_mosaic(frame)
+            
+            results['mosaic_before'] = (self.state.mosaic_width, self.state.mosaic_height)
+            appends_before = self.state.append_count
+            
+            self.motion.set_speed(self.config.scan_speed_index)
+            time.sleep(0.1)
+            
+            self.running = True
+            scan_dir = ScanDirection.RIGHT if direction == 'right' else ScanDirection.LEFT
+            stop_reason = self._scan_direction(scan_dir)
+            self.running = False
+            
+            results['success'] = True
+            results['stop_reason'] = stop_reason
+            results['appends'] = self.state.append_count - appends_before
+            results['mosaic_after'] = (self.state.mosaic_width, self.state.mosaic_height)
+            
+        except Exception as e:
+            results['error'] = str(e)
+            self.running = False
+        
+        return results
+    
+    def get_memory_estimate(self) -> dict:
+        current_bytes = self.mosaic.nbytes if self.mosaic is not None else 0
+        max_bytes = self.config.max_mosaic_width * self.config.max_mosaic_height * 3
+        
+        return {
+            'current_size': (self.state.mosaic_width, self.state.mosaic_height),
+            'current_mb': current_bytes / (1024 * 1024),
+            'max_size': (self.config.max_mosaic_width, self.config.max_mosaic_height),
+            'max_mb': max_bytes / (1024 * 1024),
+        }